Traditional models and/or techniques for calibrating data adjust and/or modify projection weights for the purpose of improving upon the accuracy of estimates that may be yielded from applying the projection weights to panelist and/or reporting data (e.g., survey data). The goal of such traditional calibration models and/or techniques is to adjust and/or modify the projection weights such that the weighted totals and/or results of the panelist and/or reporting data closely match known totals and/or results of reference and/or benchmark data (e.g., census data).
Traditional calibration models and/or techniques are executed and/or performed in a “hard” manner, whereby the projection weights are adjusted and/or modified such that the estimated totals of the panelist and/or reporting data match exactly with the known totals of the reference and/or benchmark data. Such traditional models and/or techniques for calibrating data are accordingly referred to herein as “hard calibration” models and/or techniques.
Certain examples are shown in the above-identified figures and described in detail below. In describing these examples, identical reference numbers are used to identify the same or similar elements. The figures are not necessarily to scale and certain features and certain views of the figures may be shown exaggerated in scale or in schematic for clarity and/or conciseness.